Memory-based reasoning applied to english pronunciation

  • Authors:
  • Craig W. Stanfill

  • Affiliations:
  • Thinking Machines Corporation, Cambridge, MA

  • Venue:
  • AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 2
  • Year:
  • 1987

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Abstract

Memory-based Reasoning is a paradigm for AI in which best-match recall from memory is the primary inference mechanism. In its simplest form, it is a method of solving the inductive inference (learning) problem. The primary topics of this paper are a simple memory-based reasoning algorithm, the problem of pronouncing english words, and MBRtalk, a program which uses memory-based reasoning to solve the pronunciation problem. Experimental results demonstrate the properties of the algorithm as training-set size is varied, as distracting information is added, and as noise is added to the data.